I’ve been teaching college Earth science courses as a part-time faculty member for a long time now, all while juggling other jobs. I started because it was enjoyable; no one gets into this line of work for the famously poor pay or complete lack of job security. Working with students is just one of those genuinely fulfilling experiences that is addictive enough that they ought to warn people about it.
But thanks to generative AI, it has become mostly miserable―at least in certain settings.
For the last few years, I’ve been exclusively teaching asynchronous online courses, meaning recorded videos rather than live sessions. These have always been a bit more challenging than face-to-face classes, where you have a greater ability to keep the students on track. If a student doesn’t have to show up in a room for an hour at a scheduled time and no one can see their involuntary facial expressions when they don’t understand something, the probability increases greatly that they’ll just… fall off.
But since the appearance of ChatGPT, the instructor’s job isn’t just to teach the subject and frantically attempt to keep every student’s plate spinning. Increasingly, it’s to moonlight as a detective and prosecutor because students without the motivation to do the work don’t have to skip it anymore. They can turn in a work-shaped simulacrum almost as easily. And a substantial number do—in a recent College Board survey of 600 high school students, 84 percent said they had used generative AI for schoolwork.
Teachers are certainly no strangers to cheating. But peeking at concealed notes during an exam or plagiarizing paragraphs from Wikipedia are quaint stone tools compared to the WMDs known as LLMs. I long for the binary comfort of a simple problem like “cheating or not?” Now, I’m forced to adjudicate 256 shades of gray and provide sufficient documentation to defend my decision in case a student appeals my grading to multiple levels of institutional review panels.
Not only does this soul-crushing work consume a shockingly large percentage of my time, but it leaves me with the disturbing thought that even my engaged students might not be what they seem. Maybe they grasped that difficult concept because of my help, or maybe they just laundered an LLM’s regurgitation of Wikipedia paragraphs more skillfully than I can detect.
Students often carry misconceptions about coursework. They may view an instructor as an opponent standing in the way of the grade they want. And they see “getting the right answers” as the goal of education because that’s how you secure that grade. But that’s no more true than thinking that logging a count of reps is the goal of bodybuilding. The hard work of lifting weights is the point because that yields physical results. A popular analogy is that using an LLM to write your essay is like driving a forklift into the weight room. Weights get lifted, sure, but nothing is accomplished.
If there’s no friction, no effort, then no work occurred, and the student hasn’t learned. They would have been no less productive watching paint dry. Some questions in my course assignments require critical thought to extend ideas beyond the material I’ve taught. For example, one asks them to stumble on the concept of a natural experiment by thinking of a way to study wind erosion without waiting many lifetimes for a particular boulder to erode. Before ChatGPT, about one in three successfully figured it out. For the past two years, the success rate has climbed to over half. There’s no great mystery here: The terms ChatGPT uses when prompted with this question now appear frequently.
Many instructors are trying to adapt to this crisis by going back to the only evaluation tools that are pretty much LLM-proof—tests like oral exams or handwritten work created under supervision in the classroom. None of these solutions are available to instructors of asynchronous online classes. That sucks, since the availability of those classes is important. They can serve students with physical disabilities, students in rural areas far from a campus, or students trying to obtain a degree while working full-time jobs or caring for dependents.
I’m not alone in feeling exasperated by this predicament. A survey of about 3,000 college faculty showed that 85 percent felt LLMs “make students less likely to develop critical thinking abilities,” and 72 percent reported challenges managing LLM use. Predictably, the response from higher education administrators has been to tell instructors that their job is to teach students “how to use AI effectively.”
It doesn’t seem like anyone wants to listen to instructors explain how bad it feels to try to do our job in the presence of this annihilative education antimatter. Instead, we’re offered AI grading tools to score AI-generated submissions for AI-generated assignments. I haven’t encountered any students who think they’re learning when they let LLMs do their work. It’s just workload management to them. While AI is here, it certainly isn’t revolutionizing education and enhancing learning. It’s just making it extraordinarily difficult to do all the things that have been helping students learn for a very long time.
